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From Enrico Minack <>
Subject Re:
Date Mon, 02 Mar 2020 08:15:53 GMT
Looks like the schema of some files is unexpected.

You could either run parquet-tools on each of the files and extract the 
schema to find the problematic files:

|hdfs |||-stat "%n"| 

while read file
    echo -n "$file: "
    hadoop jar parquet-tools-1.9.0.jar schema $file


Or you can use Spark to investigate the parquet files in parallel:


   .map {case (path, _) =>
     import collection.JavaConverters._
val file = HadoopInputFile.fromPath(new Path(path), new Configuration())
     val reader =
     try {
       val schema = reader.getFileMetaData().getSchema
         schema.getName, => (
           Option(f.getId).map(_.intValue()), f.getName, Option(f.getOriginalType).map(,
     }finally {
   .toDF("schema name", "fields")

.binaryFiles provides you all filenames that match the given pattern as 
an RDD, so the following .map is executed on the Spark executors.
The map then opens each parquet file via ParquetFileReader and provides 
access to its schema and data.

I hope this points you in the right direction.


Am 01.03.20 um 22:56 schrieb Hamish Whittal:
> Hi there,
> I have an hdfs directory with thousands of files. It seems that some 
> of them - and I don't know which ones - have a problem with their 
> schema and it's causing my Spark application to fail with this error:
> Caused by: org.apache.spark.sql.execution.QueryExecutionException: 
> Parquet column cannot be converted in file 
> hdfs://

> <>.

> Column: [price], Expected: double, Found: FIXED_LEN_BYTE_ARRAY
> The problem is not only that it's causing the application to fail, but 
> every time if does fail, I have to copy that file out of the directory 
> and start the app again.
> I thought of trying to use try-except, but I can't seem to get that to 
> work.
> Is there any advice anyone can give me because I really can't see 
> myself going through thousands of files trying to figure out which 
> ones are broken.
> Thanks in advance,
> hamish

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